Unstructured databases are becoming a popular alternative to conventional relational databases due to the relaxed format for data storage and the wider range of data structures that may be stored. In contrast to conventional relational databases, where strong typing imposes data constraints to adhere to a predetermined row and column format, unstructured databases impose no such restrictions.
Unstructured and semi-structured databases are gaining popularity because they permit analytical analysis with relaxed type and inclusion rules common in traditional tabular databases. In contrast to rigidly structured databases, unstructured databases permit loosely defined collections of data to aggregate data values according to named fields without imposing data type or inclusion restrictions on each documents or records included in the collection. Typically, unstructured databases take the form of a collection of documents defined according to a possibly hierarchical arrangement of subdocuments, such that each document includes one or more fields. The collections may be expressed as scripted text and syntax such as JSON (Javascript Object Notation), which permits each data collection to be human readable and editable via a standard ASCII text file. The unstructured nature also permits substantially large collections of data since each document need not conform to other documents in terms of field membership.